Anchored narratives and dialectical argumentation

Trying criminal cases is hard. The problem faced by a judge in court can be phrased in a deceptively simple way though, as follows: in order to come to a verdict, a judge has to apply the rules of law to the facts of the case. In a naïve and often criticized model of legal decision making (reminding of the bouche de la loi view on judges), the verdict is determined by applying the rules of law that match the case facts. This naïve model of legal decision making can be referred to as the subsumption model. A problem with the subsumption model is that neither the rules of law nor the case facts are available to the legal decision maker in a sufficiently well-structured form to make the processes of matching and applying a trivial matter. First, there is the problem of determining what the rules of law and the case facts are. Neither the rules nor the facts are presented to the judge in a precise and unambiguous way. A judge has to interpret the available information about the rules of law and the case facts. Second, even if the rules of law and the case facts would be determined, the processes of matching and applying can be problematic. It can for instance be undetermined whether some case fact falls under a particular rule's condition. Additional classificatory rules are then needed. In general, it can be the case that applying the rules of law leads to conflicting verdicts about the case at hand, or to no verdict at all. In the latter situation, it is to the judge's discretion to fill the gap, in the former, he has to resolve the conflict

Hardness of case-based decisions: A formal theory

Stare decisis is a fundamental principle of case-based reasoning. Yet its application varies in complexity and depends, in particular, on whether relevant past decisions agree, or exist at all. The contribution of this paper is a formal treatment of types of the hardness of case-based decisions. The typology of hardness is defined in terms of the arguments for and against the issue to be decided, and their kind of validity (conclusive, presumptive, coherent, incoherent). We apply the typology of hardness to Berman and Hafner's research on the dynamics of case-based reasoning and show formally how the hardness of decisions varies with time

Logical Comparison of Cases

Comparison between cases is a core issue in case-based reasoning. In this paper, we discuss a logical comparison approach in terms of the case model formalism. By logically generalizing the formulas involved in case comparison, our approach identifies analogies, distinctions and relevances. An analogy is a property shared between cases. A distinction is a property of one case ruled out by the other case, and a relevance is a property of one case, and not the other, that is not ruled out by the other case. The comparison approach is applied to HYPO-style comparison (where distinctions and relevances are not separately characterized) and to the temporal dynamics of case-based reasoning using a model of real world cases.</p

Representing and Evaluating Legal Narratives with Subscenarios in a Bayesian network

In legal cases, stories or scenarios can serve as the context for a crime when reasoning with evidence. In order to develop a scientifically founded technique for evidential reasoning, a method is required for the representation and evaluation of various scenarios in a case. In this paper the probabilistic technique of Bayesian networks is proposed as a method for modeling narrative, and it is shown how this can be used to capture a number of narrative properties. Bayesian networks quantify how the variables in a case interact. Recent research on Bayesian networks applied to legal cases includes the development of a list of legal idioms: recurring substructures in legal Bayesian networks. Scenarios are coherent presentations of a collection of states and events, and qualitative in nature. A method combining the quantitative, probabilistic approach with the narrative approach would strengthen the tools to represent and evaluate scenarios. In a previous paper, the development of a design method for modeling multiple scenarios in a Bayesian network was initiated. The design method includes two narrative idioms: the scenario idiom and the merged scenarios idiom. In this current paper, the method of Vlek, et al. (2013) is extended with a subscenario idiom and it is shown how the method can be used to represent characteristic features of narrative